Výsledky vyhledávání - "Kitahara, Itaru"

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M3D: Dual-Stream Selective State Spaces and Depth-Driven Framework for High-Fidelity Single-View 3D Reconstruction

Autor: Zhang, Luoxi, Shrestha, Pragyan, Zhou, Yu, Xie, Chun, Kitahara, Itaru

The precise reconstruction of 3D objects from a single RGB image in complex scenes presents a critical challenge in virtual reality, autonomous driving, and robotics. Existing neural implicit 3D representation methods face significant difficulties in

Externí odkaz: http://arxiv.org/abs/2411.12635

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RayEmb: Arbitrary Landmark Detection in X-Ray Images Using Ray Embedding Subspace

Autor: Shrestha, Pragyan, Xie, Chun, Yoshii, Yuichi, Kitahara, Itaru

Intra-operative 2D-3D registration of X-ray images with pre-operatively acquired CT scans is a crucial procedure in orthopedic surgeries. Anatomical landmarks pre-annotated in the CT volume can be detected in X-ray images to establish 2D-3D correspon

Externí odkaz: http://arxiv.org/abs/2410.08152

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Size Does Matter: An Experimental Study of Anxiety in Virtual Reality

Autor: Shen, Junyi, Kitahara, Itaru, Koyama, Shinichi, Li, Qiaoge

The emotional response of users induced by VR scenarios has become a topic of interest, however, whether changing the size of objects in VR scenes induces different levels of anxiety remains a question to be studied. In this study, we conducted an ex

Externí odkaz: http://arxiv.org/abs/2210.06697

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OmniVoxel: A Fast and Precise Reconstruction Method of Omnidirectional Neural Radiance Field

Autor: Li, Qiaoge, Ueda, Itsuki, Xie, Chun, Shishido, Hidehiko, Kitahara, Itaru

This paper proposes a method to reconstruct the neural radiance field with equirectangular omnidirectional images. Implicit neural scene representation with a radiance field can reconstruct the 3D shape of a scene continuously within a limited spatia

Externí odkaz: http://arxiv.org/abs/2208.06335

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Neural Density-Distance Fields

Autor: Ueda, Itsuki, Fukuhara, Yoshihiro, Kataoka, Hirokatsu, Aizawa, Hiroaki, Shishido, Hidehiko, Kitahara, Itaru

The success of neural fields for 3D vision tasks is now indisputable. Following this trend, several methods aiming for visual localization (e.g., SLAM) have been proposed to estimate distance or density fields using neural fields. However, it is diff

Externí odkaz: http://arxiv.org/abs/2207.14455

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